1. Field of the Invention
The present invention generally relates to processing and reporting demographic and transaction customer data, and more particularly to providing demographic and transaction data to a merchant based on transactions at, and beyond the merchant's own business, while protecting the privacy of customers.
2. Related Art
In the context of online shopping, click-through and conversion rates are two methods for measuring the performance of a website or the success of an online advertising campaign. A click-through rate is the number of users who clicked-on (i.e., selected) an advertisement on a web page divided by the number of times the advertisement was delivered (i.e., the number of impressions presented). A conversion rate is the ratio of users who convert content views or website visits into desired actions.
Surveys are sometimes used by merchants to correlate demographic and other segmentation information to develop online strategies that improve click-through and conversion rates. However, many merchants do not reach this goal because their online strategies are based on unreliable and hypothetical demographic data provided by such surveys.
One type of survey merchants use is designed to match demographic and other segmentation information to feedback from users regarding online advertising campaigns. However, this type of survey data can be unreliable due to “self selection”. Self-selection is a term used to indicate any situation in which individuals select themselves into a group, causing a biased sample. In many cases self-selection makes it difficult to evaluate programs, to determine whether the program has some effect, and to do market research because of these biases.
Another way in which merchants seek to improve click-through and conversion rates is by targeting their advertising and developing online strategies based on how site visitors behave, for example, by analyzing click-through patterns. While such behavioral targeting is generally considered useful, it still often fails to provide merchants with sufficient demographic and transaction data needed to create a robust online strategy.
Demographic data on visitors of a particular merchant website also is available. This type of data has been found to be limited, however, primarily because it lacks a correlation between the demographic data of customers and transaction data beyond the particular merchant's website from which the survey was administered. Moreover, tracking when a customer views a product at a particular merchant's website, abandons purchasing the product, and later purchases that product from a competitor requires specialized software applications.
In addition to the above challenges, customers are typically adverse to data aggregation regarding their actions and behaviors, online or otherwise. Such privacy concerns, can cause people to respond inaccurately or simply not participate in a survey.
As a result of the foregoing, merchants are hindered from acquiring rich demographic and transaction data associated with transaction data at, and beyond the particular merchant's own business, while protecting the privacy of the customers.